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  • Title: Multiagent Soft Actor-Critic Based Hybrid Motion Planner for Mobile Robots.
    Author: He Z, Dong L, Song C, Sun C.
    Journal: IEEE Trans Neural Netw Learn Syst; 2023 Dec; 34(12):10980-10992. PubMed ID: 35552145.
    Abstract:
    In this article, a novel hybrid multirobot motion planner that can be applied under no explicit communication and local observable conditions is presented. The planner is model-free and can realize the end-to-end mapping of multirobot state and observation information to final smooth and continuous trajectories. The planner is a front-end and back-end separated architecture. The design of the front-end collaborative waypoints searching module is based on the multiagent soft actor-critic (MASAC) algorithm under the centralized training with decentralized execution (CTDE) diagram. The design of the back-end trajectory optimization module is based on the minimal snap method with safety zone constraints. This module can output the final dynamic-feasible and executable trajectories. Finally, multigroup experimental results verify the effectiveness of the proposed motion planner.
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